P240 CDEIS score of 2 is optimal cut-off associated with lower risk of disease progression in early Crohn’s disease: Data from the CALM study
Bibliographic record
Abstract
Abstract Background The optimal endoscopic target in early Crohn’s disease (CD) that limits long-term disease complications is unknown. Methods We analysed medical records from patients who had follow-up data since the end of CALM. Patients with Crohn’s disease endoscopic index of severity (CDEIS) scores at the end of CALM were included. The primary outcome was a composite of major adverse outcomes reflecting CD progression: new internal fistula/abscess, stricture, perianal fistula/abscess, CD hospitalisation, or CD surgery since the end of CALM. We compared median CDEIS and per cent improvement from baseline CDEIS. Youden index analysis was used to identify optimal CDEIS cut-off score associated with CD progression. Kaplan–Meier and Cox regression methods were used to compare rates of progression by different CDEIS targets. Multivariable models were adjusted for age, prior surgery, and stricturing behaviour. Results 110 patients with median age 28 (IQR 22–38) years, disease duration 0.2 (0.1–0.5) years, and median follow up of 3.1 (1.9–4.4) years were included. Eleven per cent had a history of stricture, 5.5% history of surgery, and 52% were originally in the tight control arm of the CALM study. Median CDEIS score at end of CALM was 3 (0–5.4) and 32 (29%) patients had disease progression. Baseline median CDEIS score was similar between those with and without progression [10.9 (7.5–15.5) vs. 11.9 (8–17.5)]. Median CDEIS score at the end of CALM was higher among those with progression [1.3 (0–5.1) vs. 4.9 (3–9.1), p < 0.001)]. Patients within higher quartiles of CDEIS score had higher rates of progression over time (Figure 1). Patients without disease progression had a greater median decrease in CDEIS score from baseline to end of CALM [90% (60–100%) vs. 50% (30–80%), p < 0.001]. The optimal CDEIS score cut-off was 2 with sensitivity 84%, specificity 60% and NPV 90% for progression. Patients with CDEIS ≤ 2 had less progression over time compared with patients with > 50% improvement from baseline CDEIS (not reaching CDEIS ≤ 2) and those not meeting either endpoint (Figure 2). On adjusted analysis, CDEIS score ≤ 2 was associated with a decreased risk of progression (aHR 0.23, 95% CI 0.09–0.56). Conclusion In early CD, a CDEIS score ≤ 2 is optimal cut-off associated with a lower risk of disease progression.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".